Computational 2D Materials Scientist (Low-Temp Plasma)

Fusion Energy Base; Princeton (NJ); On-site; USD 111,000 - 178,000; Full time

Job summary

Princeton Plasma Physics Laboratory (PPPL) is seeking a Computational Scientist to advance modeling and physics research on low-temperature plasmas for processing 2D materials. The role emphasizes DFT/ab initio MD, ML potentials, and connecting simulations to experimental materials properties.

The candidate should publish results, collaborate across academia and industry, and contribute to proposal ideation and new computational capabilities.

Qualifications

• Ph.D. in Physics, Engineering or a related field with core training in low-temperature plasma physics and high-performance computing.
• Minimum 3 years of professional experience in an academic, scientific, or R&D environment.
• A proven track record of publishing original results in peer-reviewed scientific journals.
• Demonstrated collaborative experience within academia and with industry.
• Knowledge, Skills, and Abilities: Extensive practical experience using first-principles methods to study materials relevant to microelectronics, quantum devices, and plasma assisted processing, including ab initio molecular dynamics and classical molecular dynamics simulations.
• Strong ability to connect atomistic simulation results to experimentally relevant materials properties and processing outcomes, including defect formation, surface functionalization, selective etching, plasma‑induced damage, optoelectronic properties, surface cleaning, and modification of 2D materials.
• Practical knowledge of low-temperature plasma processing of materials, including plasma-assisted etching, ion/surface interactions, fluorination, oxygen and hydrogen surface chemistry, plasma activated desorption, and highly selective or self-limiting processes relevant to nanofabrication of microelectronics and quantum-device materials.
• Ability to develop computational workflows that support optimization of plasma processing conditions and interpretation of experimental observations.
• Advanced experience with major electronic structure, molecular dynamics, and quantum chemistry software packages, including VASP, CP2K, Gaussian, Quantum ESPRESSO, LAMMPS, and related atomistic modeling tools.
• Strong record of scientific publication and conference presentation in electronic structure calculations, 2D materials, defects, and plasma‑assisted processing of 2D materials.
• Ability to communicate complex computational results clearly to scientific, engineering, experimental, academic, and industrial audiences.
• Demonstrated ability to work collaboratively in multidisciplinary research environments involving theory, computation, experiment, and industry‑relevant materials processing applications.
• Ability to contribute to proposal ideation, preparation of research plans, development of new computational capabilities, and dissemination of results through peer‑reviewed publications, talks, and major international conferences.
• Experience in Molecular Dynamics Study of Plasma related materials like Liquid Lithium (and Boron) Interaction with H, D, and Impurities.

Responsibilities

• Application of ab initio molecular dynamics to low-temperature plasmas for processing of two-dimensional materials and associated technologies. The capabilities will be deployed for optimization of processing techniques of these materials.
• Defining and delivering on A.I. projects for low-temperature plasmas (20%).
• Proposal ideation and preparation (10%).
• Modeling plasma processing for industry partners (20%).
• Publishing scientific results and dissemination at major international conferences (10%).

Skills

DFT modeling

MD simulations

2D materials

ab initio MD

machine learning potentials

VASP

CP2K

Gaussian

Quantum ESPRESSO

LAMMPS

communication

collaboration

Education

PhD in Physics, Engineering or related field

Tools

VASP

CP2K

Gaussian

Quantum ESPRESSO

LAMMPS

Job description

Princeton Plasma Physics Laboratory (PPPL) is seeking a Computational Scientist to advance modeling and physics research on low-temperature plasmas for processing 2D materials. The role emphasizes DFT/ab initio MD, ML potentials, and connecting simulations to experimental materials properties.

The candidate should publish results, collaborate across academia and industry, and contribute to proposal ideation and new computational capabilities.